{"id":"W4308381125","doi":"10.1145/3548606.3560559","title":"Selective MPC","year":2022,"lang":"en","type":"article","venue":"Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Computation; Key (lock); Server; Noise (video); Secure multi-party computation; Protocol (science); Distributed computing; Theoretical computer science; Algorithm; Artificial intelligence; Computer network; Computer security","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0005348445,0.0001738473,0.000221172,0.0001475273,0.001178171,0.0001880656,0.007690365,0.00003884314,0.00003092561],"category_scores_gemma":[0.0000639109,0.0001521761,0.0001189945,0.001020382,0.0002426019,0.000385082,0.01246905,0.0007406935,0.000001750249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000419254,"about_ca_system_score_gemma":0.00008140936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004645907,"about_ca_topic_score_gemma":0.00001104655,"domain_scores_codex":[0.9985734,0.0001004627,0.0002829494,0.0004113199,0.0004102323,0.0002216679],"domain_scores_gemma":[0.9974639,0.0002359487,0.0002507615,0.001693482,0.0002810038,0.00007492554],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00001466191,0.0003237242,0.001800242,0.00002270639,0.00003232823,1.182818e-7,0.003886922,0.000002595597,0.0003921504,0.9830682,0.003429742,0.007026577],"study_design_scores_gemma":[0.0007884406,0.0006653143,0.01339844,0.00006033137,0.00003780956,0.00005071433,0.001026046,0.09673559,0.001739033,0.8662423,0.01866479,0.0005912174],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8247365,0.003283055,0.02996483,0.07760451,0.00213194,0.003936871,0.0008672461,0.001272096,0.056203],"genre_scores_gemma":[0.98632,0.0001895916,0.01284639,0.0004983412,0.00002172909,0.0001008293,0.000007874556,0.000006713224,0.000008492646],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1615836,"threshold_uncertainty_score":0.9976785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02669104726638954,"score_gpt":0.2549065721040585,"score_spread":0.2282155248376689,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}